How healthcare companies report results: ARPOB, occupancy and same-store growth explained

A hospital or a diagnostics chain does not sell one product at one price the way a manufacturer does, so its results are read through a different set of numbers: how full its beds or labs are, what it earns per patient or per test, and how the existing network is growing versus how much of the growth is new capacity.

Hospital metrics

• Occupancy (or occupancy rate): operational beds actually in use, as a percentage. A hospital’s revenue depends on both how many beds it has and how full they are.
• Average length of stay: how many days, on average, a patient stays. It affects both occupancy and revenue per patient.
• ARPOB (average revenue per operating bed): hospital revenue divided by patient days, where patient days is the number of occupied beds multiplied by the number of days in the period. It blends price, occupancy and length of stay into one figure, which is why two hospitals can show the same revenue growth for different underlying reasons. Not every chain reports it the same way going forward: Apollo Hospitals, for instance, moved to an average-revenue-per-patient measure from FY26 instead. Check which measure a company uses before comparing it with another hospital’s ARPOB.
• Case mix: the split of patients across specialities and procedure types. A shift toward more complex, higher-value procedures can raise ARPOB without any change in occupancy.

Diagnostics (pathology and lab-testing) metrics

• Test volume: the number of tests processed in the period, the diagnostics equivalent of units sold.
• Realisation per test: revenue divided by test volume — how much the company earns, on average, for each test. A shift toward specialised or higher-value tests raises this even if the number of routine tests is flat.
• Same-store (or same-lab) growth: revenue growth from labs and collection centres that were already operating in the comparable period a year earlier, separated from revenue added purely by opening new locations. Companies don’t always use this exact label — a results presentation may instead just split “patient volumes” or revenue by existing versus newly added locations; the underlying split is the same idea.
• Payor mix (or B2C/B2B mix): the split between patients paying directly (cash/retail, often labelled B2C) and those billed through insurers, corporates or government schemes (institutional, often labelled B2B). The mix affects both pricing and how quickly the company is paid.

An illustrative example (hospital)

A fictional hospital operator, in ₹ crore, for one quarter:

	This year	Last year
Operational beds	1,000	900
Occupancy	65%	62%
Patient days	59,150	50,778
Revenue	592	460
ARPOB (revenue ÷ patient days, ₹/day)	≈ 100,000	≈ 90,000

Revenue rose about 28.7% here, but that came from three different sources at once: more beds (1,000 versus 900), better occupancy (65% versus 62%), and a higher ARPOB (roughly 100,000 versus 90,000). Reading the revenue line alone would not show which of the three did the work — a hospital that only added beds is a different story from one that filled its existing beds more fully or earned more per bed.

Reading a diagnostics result the same way

The equivalent check for a diagnostics chain is to separate test-volume growth (are more tests being done, including at existing labs) from realisation growth (is each test earning more), and to check how much of total growth is same-store versus from labs and collection points opened during the period.

Related: the complete guide to reading a quarterly result and year on year vs quarter on quarter.